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Bayes-cost reduction algorithm in quantum hypothesis testing (Corresp.)

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1 Author(s)

An iterative procedure is described for reducing the Bayes cost in decisions among M> 2 quantum hypotheses by minimizing the average cost in binary decisions between all possible pairs of hypotheses: the resulting decision strategy is a projection-valued measure and yields an upper bound to the minimum attainable Bayes cost. From it is derived an algorithm for finding the optimum measurement states for choosing among M linearly independent pure states with minimum probability of error. The method is also applied to decisions among M unimodal coherent quantum signals in thermal noise.

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Information Theory, IEEE Transactions on  (Volume:28 ,  Issue: 2 )